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Sewing is the most widely used and preferred method for manufacturing clothing products for extreme weather conditions and other industrial insulation systems. Multiple layers of functional fabrics in combination with insulation materials are used to thermally insulate precious body heat from its surrounding cold environment. The sewing process fixes the insulation material between the fabric layers. During conventional sewing, the insulation material is compressed along the stitch line. With the compression of the insulation material, entrapped air is forced to leave the insulation material internal structure, and heat loss occurs along the entire length of the stitch line. It results in the deterioration of thermal properties of the end product along the stitch line.

The amount of air, which is a decisive factor for thermal properties of any insulation system, was investigated at the level of a unit stitch length of a lockstitch. Conventional microscopy methods are not suitable to study the compression along the stitch line. With the help of X-ray tomography, the three-dimensional data of a stitch was taken and studied to measure the volume of air. The samples were prepared with conventional lockstitch sewing and a newly developed innovative sewing method “Spacer Stitching.” The results are compared with each other in terms of the amount of air present in a unit stitch length.

Calculations based on X-ray tomography images of lockstitch and spacer stitch revealed that, in the case of lockstitch, a unit stitch has a 15% of its volume made up of material and 85% of its volume by air. In comparison, the spacer stitch with the same sewing and fabric parameters has a material volume of 4.6 % and an air volume of 95.4% in a single stitch.

The research can positively improve the thermal properties of sewn material made for insulating purposes of conventional clothing as well as of industrial insulations.

There is no literature available which investigates and calculates the amount of air and material present along with a stitch line.

A study of thread tensions on a lockstitch sewing machine was made, measuring simultaneously both the needle and bobbin thread tensions. Experiments were carried out under specified sewing conditions, whereby needle and bobbin thread tensioner adjustment, sewing speed, number of plies, fabric quality and sewing thread quality were varied in order to investigate the effect of these factors on the needle and bobbin thread tensions. The patterns of the thread tension traces obtained were analysed as well as the effect of these factors on the peak tensions detected on both thread tension traces. Four significant peak tensions on the needle thread tension trace and two significant peak tensions on the bobbin thread tension trace were detected, during a stitch cycle. It was found that no significant variations occurred as far as the timing and shape of the peak tensions were concerned. However, variations were detected in the peak tensions according to the sewing conditions, as expected. From the analysis of the data obtained, multiple regression equations were derived to predict, with a good degree of accuracy, the peak tensions generated, according to the sewing conditions.

The stitch formation process of a lockstitch sewing machine has been investigated with the aid of transducers which facilitate real-time monitoring of the sewing cycle. It has been found that increasing the travel of the check-spring by three millimetres from the normal position significantly reduces needle thread consumption per stitch and increases the peak dynamic needle thread tension. This change in lockstitch formation has a profound effect on the geometry of the stitch and the theoretical performance of the stitch under longitudinal load. The ability to reduce static thread tension settings after extending the check-spring travel can be employed as a remedy for tension induced seam pucker.

A study of thread tensions on a lockstitch sewing machine was made, measuring simultaneously both the needle and bobbin thread tensions. Investigates the relationship between the peak tensions generated during the experiments and the corresponding seam balance. It was found that under the conditions of the experiments it is possible to define an envelope of conditions under which balanced seams will be obtained.

Seam efficiency plays an important role for obtaining a desired seam quality. Therefore, this issue is often referred in research papers. The purpose of this paper is to determine the seam strength and efficiency as well as examining, if and how such factors as: a kind of fabric, kind of thread, kind of seam and the stitch density influence the transverse seam strength and the seam efficiency.

For research four types of polyester/wool fabrics having different structural parameters and two types of polyester sewing threads were used. Three types of seam were made. The fabric samples were sewn using lockstitch with three different stitch densities. Obtained in this way seams were tested on the tensile machine. The influence of individual factors on the seam strength and its efficiency was assessed statistically using a multivariate variance analysis (ANOVA).

The findings of this study revealed that the independent variable – stitch density affect significantly of the seam strength as well as its efficiency. Seam strength and seam efficiency values increase with the increase stitch density. Moreover, the variance analysis showed that a kind of fabric also is a statistically significant factor for the seam efficiency and its strength. Furthermore, in the case of seam efficiency it is also important to the stitch direction. However, the study did not show an impact of kind of thread and kind of seam on dependent variables: the seam strength and its efficiency.

Due to the fact that this paper focuses on the seams made only on wool/polyester fabrics with two the most popular weaves, involving only two sewing PES threads, the conclusions presented in this paper are valid only to this assortment and cannot be generalized.

So far, it has not been taken research on the effect of seams with the different number of sewn layers on the seam strength and efficiency. This issue has been taken in this work.

The purpose of this paper is to develop and test control methods for real‐time automatic presser‐foot force control in industrial sewing machines. In this work, a closed‐loop controller that controls presser‐foot maximum vertical displacement is presented and compared to existing solutions that adjust force depending on sewing speed. Automatic force control can reduce problems such as stitch irregularity, stitch distortions and material damage, besides making material handling easier.

An electromagnetic force actuator was integrated in an industrial lockstitch machine. A computer‐based control system was designed implementing either speed‐variable force control, closed‐loop control, or emulating a traditional constant‐force system. Maximum presser‐foot displacement values were measured and analysed in relevant sewing situations, and seam quality was assessed.

Constant‐force control does not allow optimal force setting at all speeds. Speed‐variable force control is an improvement, but requires empirical setting of the speed‐force relation, not always assuring optimal operation. Closed‐loop control adapts force to the requirement of each sewing situation more precisely. Sewing quality is good and material handling is eased.

The actuator has to be optimised regarding response time and maximum force. Some aspects in the behaviour of the control system and actuator have to be further studied.

The proposed control system enables the automatic setting and adaptation of force to all sewing situations, making material handling easier at low speeds without compromising feeding performance at high speed. The closed‐loop controller may be used as a teach‐in system for speed‐dependent control.

This is the first prototype of a closed‐loop control system for presser‐foot force on a lockstitch sewing machine and the first comparative study of control methods for presser‐foot force control.

This paper aims to develop a single regression model (instead of developing models separately for each thread type) to predict the sewing thread consumption for cotton and polyester staple spun threads.

A single regression model is developed for predicting sewing thread consumption for cotton and polyester threads. The polyester sewing threads have lower sewing thread consumption as compared to cotton threads because of their higher elongation behaviour. The model differentiates between the cotton and polyester sewing threads using their elongation values at peak levels of tensions experienced by the sewing threads during stitch tightening. By comparing the estimated thread consumption values with actual values, the effectiveness of model is evaluated with root mean square error and coefficient of determination (R²).

During the sewing process, by understanding the behaviour of different types of sewing threads, it is possible to develop a single regression model for all types of threads.

The sewing thread consumption can be easily calculated for cotton and polyester sewing threads using a single regression equation using the sewing assembly thickness, stitch density and elongation of thread at peak tension. The garment manufacturers need not depend on different charts for sewing thread consumption for stock management.

The sewing thread consumption is different for different types of threads, and garment manufacturers have to depend on different charts given by sewing thread manufacturers or use different equations for each type of threads. Using this single regression equation, sewing thread consumption for cotton and polyester sewing thread can be estimated accurately.

This paper aims to develop at sewing thread during the seam formation may lead to the compression of fabric under seam. In the present study, the model has been proposed to predict the seam compression and calculation of seam boldness, as well as thread consumption by considering seam compression.

The effect of sewing parameters on the fabric compression at the seam (Cf) for fabrics of varying bulk density was studied by the Taguchi method and also the multilinear regression equation is obtained to predict seam compression by considering these parameters. The framework has been set as per the single view metrology approach to measuring structural seam boldness (Bs). One of the basic geometrical models (Ghosh and Chavhan, 2014) for the prediction of thread consumption at lock stitch has been modified by considering fabric compression at the seam (Cf).

The multilinear regression model has been proposed which can predict the compression under seam using easily measurable fabric parameters and stitch density. The seam boldness is successfully calculated quantitatively using the proposed formula with a good correlation with the seam boldness rated subjectively. The thread consumption estimation from the proposed approach was found to be more accurate.

The compression under seam is found out using easily measurable parameters; fabric thickness, fabric weight and stitch density from the proposed model. The attempt has been made to calculate seam boldness quantitatively and the new approach to find out thread consumption by considering the seam compression has been proposed.

This paper aims to propose the artificial neural network (ANN) and regression models for the estimation of the thread consumption at multilayered seam assembly stitched with lock stitch 301.

In the present study, the generalized regression and neural network models are developed by considering the fabric types: woven, nonwoven and multilayer combination thereof, with basic sewing parameters: sewing thread linear density, stitch density, needle count and fabric assembly thickness. The network with feed-forward backpropagation is considered to build the ANN, and the training function trainlm of MATLAB software is used to adjust weight and basic values according to the optimization of Levenberg Marquardt. The performance of networks measured in terms of the mean squared error and the layer output is set according to the sigmoid transfer function.

The proposed ANN and regression model are able to predict the thread consumption with more accuracy for multilayered seam assembly. The predictability of thread consumption from available geometrical models, regression models and industrial empirical techniques are compared with proposed linear regression, quadratic regression and neural network models. The proposed quadratic regression model showed a good correlation with practical thread consumption value and more accuracy in prediction with an overall 4.3% error, as compared to other techniques for given multilayer substrates. Further, the developed ANN network showed good accuracy in the prediction of thread consumption.

The estimation of thread consumed while stitching is the prerequisite of the garment industry for inventory management especially with the introduction of the costly high-performance sewing thread. In practice, different types of fabrics are stitched at multilayer combinations at different locations of the stitched product. The ANN and regression models are developed for multilayered seam assembly of woven and nonwoven fabric blend composition for better prediction of thread consumption.

The purpose of this investigation was to try to develop a theoretical model to satisfy and explain the interaction between the needle and bobbin threads, the tensions developed and their influence on seam balance. An explanation of the conditions determining seam balance is proposed based on a “robbing back” theory of stitch formation.